Using machine learning to accelerate ecological research | DeepMind

The Serengeti is one of the last remaining sites in the world that hosts an intact community of large mammals. These animals roam over vast swaths of land, some migrating thousands of miles across multiple countries following seasonal rainfall. As human encroachment around the park becomes more intense, these species are forced to alter their behaviours in order to survive. Increasing agriculture, poaching, and climate abnormalities contribute to changes in animal behaviours and population dynamics, but these changes have occurred at spatial and temporal scales which are difficult to monitor using traditional research methods. There is a great urgency to understand how these animal communities function as human pressures grow, both in order to understand the dynamics of these last pristine ecosystems, and to formulate effective management plans to conserve and protect the integrity of this unique biodiversity hotspot.

6 mentions: @demishassabis@DeepMindAI@MichaelZielins@TKousi@SofiMinano@luckflow
Date: 2019/08/09 09:46

Referring Tweets

@demishassabis Great to see this collaboration between our Science team and ecologists, to develop an AI tool to help speed up much needed conservation research in the Serengeti! The team will be presenting this work at @DeepIndaba later this month
@DeepMindAI In our latest blog post, we detail a collaboration with ecologists and citizen scientist volunteers who led to the development of an automated animal counting tool that could help accelerate conservation research in the Serengeti.
@MichaelZielins Excited to be able to share how we are collaborating with ecologists to help support their efforts in Serengeti National Park in Tanzania.

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